TítolDynamic anonymous index for confidential data
Publication TypeConference Paper
Year of Publication2014
AuthorsNavarro-Arribas G, Abril D, Torra V
EditorGarcia-Alfaro J, Lioudakis G, Cuppens-Boulahia N, Foley S, Fitzgerald WM
Conference NameData Privacy Management and Autonomous Spontaneous Security
ISBN Numberisbn=978-3-642-54567-2
Paraules claudynamic anonimization

In this paper we introduce a k-anonymous vector space model, which can be used as an index of a set of confidential documents. This model allows to index, for example, encrypted data. New documents can be added or removed while maintaining the k-anonymity property of the vector space.